Improving the accuracy of soil moisture retrievals using the phase difference of the dual-polarization GNSS-R interference patterns

Soil moisture (SM) is a key parameter in the climate studies at a global scale and a very important parameter in applications such as precision agriculture at a local scale. The Global Navigation Satellite Systems Interference Pattern Technique (IPT) has proven to be a useful technique for the determination of SM, based on observations at vertical polarization (V-Pol) due to the Brewster angle. The IPT can be applied at both V-Pol and horizontal polarization (H-Pol) at the same time, observing the Brewster angle only at V-Pol. This letter presents a measurement technique based on tracking the phase difference between V-Pol and H-Pol interference patterns to improve the accuracy of the Brewster angle determination and, consequently, that of the SM retrievals. This technique benefits from the different phase behavior of the reflection coefficients between H-Pol and V-Pol in the angular observation range. To be sensitive to the phase difference, the Rayleigh criterion for smooth surfaces must be accomplished. This technique is not sensitive to topography as it is intrinsically corrected. Experimental results are presented to validate the proposed algorithm.Peer ReviewedPostprint (author’s final draft

Contributions to land, sea, and sea ice remote sensing using GNSS-reflectometry

This PhD thesis researches the use of passive remote sensing techniques using signals transmitted from the navigation satellites (GNSS) in order to retrieve different geophysical parameters. The thesis consists of two different parts without taking into account the introduction, the state of the art and the conclusions. The first part analyzes the Interference Pattern Technique (IPT), which was previously used in another PhD thesis, and proposes some key improvements. First, the addition of horizontal polarization to the existing vertical polarization is proposed. Then, the retrieval of soil moisture is studied using the horizontal polarization only and combining both polarizations to correct for the surface roughness effects. It is also demonstrated that the phase difference between the two interference patterns is directly related to soil moisture content. A field campaign was conducted in Australia to test empirically all the theoretical developments and algorithms. Secondly, the possibility of measuring Significant Wave Height (SWH) and Mean Sea Surface Level (MSSL) using the IPT is studied. A three month field campaign over coastal sea is devoted to that study. The SWH retrieval is a new estimation algorithm based on measuring the point where the interference pattern loses coherence. The MSSL retrieval is based on the estimation of the IPT oscillation frequency, testing different spectral estimators to improve the accuracy. Since the IPT is limited in coverage due to its static requirements, the research conducted in this thesis migrated to scatterometric GNSS-R techniques. The main goal that migration was to increase coverage of the different GNSS-R instruments. Therefore, the second part of this thesis analyzes the applicability of a scatterometric technique from different platforms: ground-based (mobile and fixed), airborne, and spaceborne. The ground-based still platforms have allowed to develop a soil moisture retrieval algorithm. The ground-based moving platforms have extended the validity of that algorithm. Airborne platforms have been used to study the reflected electric field statistics when the surface reflecting surface is varying (smooth or rough land, and sea). They have also been used to develop different algorithms to measure the coherent and incoherent scattered components depending on the data structure (real-data or complex data). Coherent reflectivity measured from airborne platforms has been compared to other techniques such microwave radiometry, which is highly used in the soil moisture retrieval from spaceborne sensors, and other sensors using optical, multispectral and thermal frequency bands. These relationships between microwave radiometry and GNSS-R measurements suggests the potential synergy of both techniques. A sea ice detection algorithm is also developed using scatterometric GNSS-R data from the UK TDS-1 mission. This algorithm is based on measuring the degree of coherence of the reflected waveform. Finally, a field campaign was conducted to study the effect of vegetation on the GNSS signals that pass through it in order to take into account and correct the effect of vegetation in the GNSS-R data and in the soil moisture retrieval algorithms.Aquesta tesi doctoral aprofundeix en el coneixement de les tècniques de teledetecció passives utilitzant senyals emesos pels satèl·lits de navegació (GNSS) amb l'objectiu de recuperar diferents paràmetres geofísics del terreny. La tesi conté dues parts ben diferenciades a banda de la introducció, estat de l'art i conclusions. La primera part analitza la tècnica coneguda com a patró d'interferències, utilitzada prèviament en una altra tesi doctoral, i proposa certes millores per la seva aplicabilitat. En primer lloc es decideix afegir polarització horitzontal a la ja existent polarització vertical, i s'estudia la recuperació d'humitat del sòl utilitzant només polarització horitzontal i combinant les dues polaritzacions per corregir els efectes de la rugositat del terreny. A continuació es demostra que la mesura de desfasament entre els dos patrons d'interferència està directament relacionada amb la humitat del terreny. Es va realitzar una campanya de mesures a Austràlia per provar empíricament tots els desenvolupaments teòrics i algorismes proposats. En segon lloc s'analitza l'aplicabilitat del patró d'interferències en la mesura de l'altura de les onades (SWH) i del nivell del mar (MSSL), tots dos de forma precisa. L'estimació de l'alçada de les onades és un procés totalment nou basat en mesurar el punt on el patró d'interferències perd la coherència. L'estimació del nivell del mar es basa en l'anàlisi espectral del patró d'interferències provant diferents estimadors espectrals. Atès que la tècnica del patró d'interferència està limitada en cobertura per les seves característiques estàtiques, la investigació duta a terme en aquesta tesi doctoral va migrar cap a tècniques GNSS-R escateromètriques. El principal objectiu a assolir va ser el d'augmentar la cobertura dels diferents instruments GNSS-R de mesura. En conseqüència, la segona part d'aquesta tesi analitza l'aplicabilitat d'aquestes tècniques des de diferents plataformes terrestres (mòbils i fixes), aerotransportades i satèl·lit. Les plataformes terrestres fixes han permès derivar algoritmes de recuperació d'humitat i les mòbils estendre la validació d'aquests. Les plataformes aerotransportades s'han utilitzat per mirar l'estadística del camp elèctric reflectit quan la superfície on es reflecteixen els senyals GNSS va variant (terra plana o terra rugosa, i mar). També han servit per desenvolupar diferents algorismes amb l'objectiu de determinar les components coherent i incoherent del senyal reflectit. De la mateixa manera, dades de reflectivitat coherent mesurades des d'aquestes plataformes han estat comparades amb altres tècniques de teledetecció passiva com la radiometria de microones, altament utilitzada en la mesura d'humitat de terreny, i altres sensors òptics, multi-espectrals, i tèrmics. Aquests resultats han permès suggerir la possible sinergia de dades d'ambdues tecnologies. Un algorisme per detectar la presència de gel sobre el mar també ha estat desenvolupat mitjançant l'ús de dades GNSS-R escateromètriques satel·litals de la missió UK TDS-1. Aquest algorisme es basa en mesurar el grau de coherència de la forma d'ona reflectida. Finalment, s'ha realitzat un estudi de l'efecte de la vegetació en els senyals GNSS que la travessen, per tal de poder corregir aquest efecte en els algoritmes de recuperació d'humitat del terreny

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version

Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security

Estimativa da umidade do solo por refletometria GNSS : uma revisão conceitual

Soil moisture monitoring enables efficient management and use of water resources, having great importance for several purposes, such as: monitoring of risk areas; delimitation of areas susceptible to flooding; geotechnical activities; and in agriculture development. GNSS Reflectometry (GNSS-R) is a scientific and technological development that allows one to perform proximal or remote sensing, depending on the antenna height concerning the surface, by means of navigation satellites. This method exploits GNSS signals indirectly reaching a receiver antenna after they are reflected on the surrounding surfaces. In this method, direct and indirect GNSS signals that reach the receiving antenna are exploited, after reflection on the surfaces existing around the antenna. The combination of these two signals causes the multipath effect, which affects GNSS observable and deteriorates positioning. On the other hand, when interacting with these reflecting surfaces one can estimate their properties. One of the main advantages of GNSS-R, when compared with the conventional methods, is the intermediate coverage area, as well as, the use of the well-defined structure of GNSS systems that guarantee appropriate temporal resolution. The scope of this paper is to present a conceptual review of GNSS-R applied to soil moisture monitoring.O monitoramento da umidade do solo possibilita o manejo e uso eficiente de recursos hídricos, sendo uma atividade importante em diversas áreas, tais como: no monitoramento de áreas de risco; delimitação de áreas suscetíveis a enchentes; atividades da geotecnia; e na agricultura. A Refletometria GNSS (GNSS-R) é um desenvolvimento científico e tecnológico que permite realizar sensoriamento remoto ou proximal, a depender da altura da antena em relação à superfície, com satélites de navegação. Neste método, explora-se os sinais GNSS que chegam à antena receptora de maneira direta e indireta, após reflexão nas superfícies existentes no entorno da antena. A combinação destes dois sinais ocasiona o efeito de multicaminho, que afeta as observáveis GNSS e deteriora o posicionamento. Por outro lado, ao interagir com estas superfícies, o sinal indireto permite estimar atributos acerca destas superfícies, como por exemplo a umidade do solo. Uma das principais vantagens em relação aos métodos convencionais reside no fato do GNSS-R proporcionar uma área de abrangência intermediária e o uso da estrutura bem estabelecida dos satélites GNSS, que garantem resolução temporal apropriada. O escopo deste trabalho é apresentar uma revisão conceitual acerca do GNSS-R aplicado no monitoramento da umidade do solo

On the correlation between GNSS-R reflectivity and L-band microwave radiometry

This work compares microwave radiometry and global navigation satellite systems-reflectometry (GNSS-R) observations using data gathered from airborne flights conducted for three different soil moisture conditions. Two different regions are analyzed, a crops region and a grassland region. For the crops region, the correlation with the I/2 (first Stokes parameter divided by two) was between 0.74 and 0.8 for large incidence angle reflectivity data (30°-50°), while it was between 0.51 and 0.61 for the grassland region and the same incidence angle conditions. For the crops region, the correlation with the I/2 was between 0.64 and 0.69 for lower incidence angle reflectivity data (<;30°), while it was between 0.41 and 0.6 for the grassland region. This indicates that for large incidence angles the coherent scattering mechanism is dominant, while the lower incidence angles are more affected by incoherent scattering. Also a relationship between the reflectivity and the polarization index (PI) is observed. The PI has been used to remove surface roughness effects, but due to its dependence on the incidence angle only the large incidence angle observations were useful. The difference in ground resolution between microwave radiometry and GNSS-R and their strong correlation suggests that they might be combined to improve the spatial resolution of microwave radiometry measurements in terms of brightness temperature and consequently soil moisture retrievals.This work was supported in part by the Spanish Ministry of Science and Innovation, “AROSA-Advanced Radio Ocultations and Scatterometry Applications using GNSS and other opportunity signals,” under Grant AYA2011-29183-C02-01/ESP and “AGORA: Tecnicas Avanzadas en Teledetección Aplicada Usando Señales GNSS y Otras Señales de Oportunidad,” under Grant ESP2015-70014-C2-1-R (MINECO/FEDER), in part by the Monash University Faculty of Engineering 2013 Seed Grant, and in part by the Advanced Remote Sensing Ground-Truth Demo and Test Facilities and Terrestrial Environmental Observatories funded by the German Helmholtz-Association. The work of A. A.-Arroyo was supported by the Fulbright Commission in Spain through a Fulbright grant.Peer ReviewedPostprint (author's final draft

Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets

Deriving vertical total electron content maps from SMOS full polarimetric data to compensate the Faraday rotation effect

The Faraday rotation is a geophysical effect that causes a rotation of the electromagnetic field components emitted by the Earth when it propagates through the ionosphere. It depends on the vertical total electron content (VTEC) of the ionosphere, the geomagnetic field, and the frequency. For satellite measurements at the L band, this effect is not negligible and must be compensated for. This is the case of the Soil Moisture and Ocean Salinity (SMOS) mission, where the measured polarimetric brightness temperature must be corrected from the Faraday rotation effect before the retrieval of the geophysical parameters. The Faraday rotation angle (FRA) can be estimated using a theoretical formulation that makes use of external sources for the VTEC and the geomagnetic field. Alternatively, it can be continuously retrieved from the SMOS full-polarimetric data. However, this is not straightforward due to the relatively poor radiometric sensitivity (thermal noise) and accuracy (spatial bias) of its payload MIRAS (Microwave Interferometer Radiometer by Aperture Synthesis). In this thesis, a methodology for estimating the total electron content of the ionosphere by using an inversion procedure from the measured rotation angle has been developed. These SMOS VTEC maps are derived from SMOS measurements in the Extended Alias-Free Field of View (EAF-FoV) by applying spatio-temporal filtering techniques to mitigate the radiometric errors present in the full-polarimetric measured brightness temperatures. Systematic error patterns found in the Faraday rotation angle retrieval have been characterized along the mission and corrected. The methodology is independent, not only of external databases and forward models, but also of the target that is being measured. Eventually, these SMOS-derived VTEC maps can then be used in the SMOS level 2 processors to improve the geophysical retrievals. The impact of using these SMOS VTEC maps to correct the FRA in the SMOS mission instead of the commonly used VTEC data from GPS has also been assessed, particularly over ocean, where the ionospheric effect is stronger. This assessment has demonstrated improvements in the spatial biases, in the stability of the brightness temperatures (especially in the third Stokes parameter), and in the reduction of the latitudinal gradient present in the third Stokes parameters. All these quality indicators point to a better quality of the geophysical retrievals.La rotación de Faraday es un efecto geofísico que causa un giro en las componentes del campo electromagnético emitido por la Tierra cuando éste se propaga a través de la ionosfera. Ésta depende del contenido vertical total de electrones (VTEC) en la ionosfera, el campo geomagnético y la frecuencia. En las medidas de los satélites que operan en banda L, este efecto no es despreciable y se debe compensar. Este es el caso de la misión SMOS (Soil Moisture and Ocean Salinity), por lo que el efecto de Faraday se tiene que corregir en las medidas polarimétricas captadas por el instrumento antes de obtener parámetros geofísicos. El ángulo de rotación de Faraday (FRA) se puede estimar con una fórmula teórica que usa bases de datos externas para el VTEC y el campo geomagnético. Alternativamente, se puede obtener de una manera continua a partir de los datos polarimétricos de SMOS. Sin embargo, esto no se logra con un cálculo directo debido a la pobre sensibilidad radiométrica (ruido térmico) y a la baja precisión (sesgos espaciales) que presenta el instrumento MIRAS (Microwave Interferometer Radiometer by apertura Synthesis), que se encuentra a bordo del satélite. En esta tesis, se desarrolla una metodología para estimar el VTEC de la ionosfera usando un proceso inverso a partir del ángulo de rotación medido. Estos mapas de VTEC se derivan de medidas en todo el campo de visión extendido en donde no hay aliasing. Para mitigar los errores radiométricos en las temperaturas de brillo polarimétricas, se aplican técnicas de filtrados temporales y espaciales. En el ángulo de rotación de Faraday recuperado se detectaron errores sistemáticos. Estos se caracterizaron a lo largo de la misión y se corrigieron. La metodología es independiente, no solo de bases de datos externas y modelos de océano, sino también de la superficie medida. Estos mapas de VTEC derivados de los datos SMOS se pueden usar en el procesador de nivel 2 para mejorar las recuperaciones geofísicas. Se ha evaluado el impacto de usar estos mapas para corregir el FRA en la misión, en vez de los datos de VTEC que comúnmente se emplean (mapas provenientes de datos de GPS), particularmente sobre océano, en donde los efectos de la ionosfera son más críticos. Esta verificación ha demostrado mejoras en el sesgo espacial, en la estabilidad de las temperaturas de brillo (especialmente en el tercer parámetro de Stokes) y en la reducción del gradiente latitudinal presente en el tercer parámetro de Stokes. Todos estos indicadores de calidad apuntan a la obtención de parámetros geofísicos de mejor calidad.Postprint (published version